1 Ocorrências da Baleia Franca Austral
As baleias francas (Eubalaena australis) podem ser facilmente distinguidas dos outros grandes cetáceos por várias características. A principal delas é a ausência da nadadeira dorsal, característica exclusiva dentre as baleias que habitam o Hemisfério Sul. Possuem os orifícios respiratórios bastante separados, originando um vapor característico em forma de “V” durante a respiração (CUMMINGS, 1985; EVANS, 1987). Além disso, esta espécie apresentam diversas calosidades ou “verrugas” na região da cabeça, as quais são utilizadas como principal caracteristica de identificação destes individuos, pois cada individuo apresenta um padrão diferente.
Esta espécie apresenta dimorfismo sexual, sendo as fêmeas maiores que os machos, podendo chegar a 18 metros de comprimento e pesando até 56 toneladas. O período de gestação é de 11 a 12 meses, no qual as fêmeas tem em média um filhote a cada três anos. Os filhotes nascem com cerca de 6 metros e pesando 4 a 5 toneladas.
Assim como outras espécies de Mysticetos, Eubalaena australis realizam movimentos de migrações durante o ano, passando o verão na região do polo Sul se alimentando e migrando para águas mais quentes durante o inverno, principalmente para desenvolverem atividades de acasalamento e procriação. Importante ressaltar que esta espécie tem ocorrência registradas em toda a área do Hemisfério Sul. Já no Hemisfério Norte tem-se a ocorrência da espécie Eubalaena glacialis, a qual sofre diversos impactos de origem antrópica.
2 Coletando Informações de Bancos de Dados Abertos
2.1 Banco de dados OBIS
Iniciamos instalando os pacotes dplyr, tidyverse e robis. Em seguida, iniciou-se o download das ocorrências e demais informações sobre a espécie E. australis. Por meio da função occurrence fez-se a busca simples das ocorrências da espécie no repositório OBIS.
## carregar pacotes
library(dplyr)
library(tidyverse)
library(robis)Em seguida, os dados foram coletados 17.131 observações com 127 variáveis.
# baixar ocorrências
franca_obis <- robis::occurrence("Eubalaena australis")
#Retrieved 17131 records of approximately 17131 (100%)# checar dados
names(franca_obis)## [1] "country" "date_year"
## [3] "scientificNameID" "scientificName"
## [5] "superfamilyid" "individualCount"
## [7] "dropped" "aphiaID"
## [9] "decimalLatitude" "subclassid"
## [11] "phylumid" "familyid"
## [13] "catalogNumber" "occurrenceStatus"
## [15] "basisOfRecord" "terrestrial"
## [17] "taxonConceptID" "superclass"
## [19] "modified" "id"
## [21] "order" "superclassid"
## [23] "infraorderid" "dataset_id"
## [25] "decimalLongitude" "date_end"
## [27] "speciesid" "occurrenceID"
## [29] "superfamily" "suborderid"
## [31] "date_start" "genus"
## [33] "eventDate" "brackish"
## [35] "absence" "taxonRank"
## [37] "genusid" "originalScientificName"
## [39] "marine" "subphylumid"
## [41] "vernacularName" "date_mid"
## [43] "class" "suborder"
## [45] "infraorder" "orderid"
## [47] "footprintWKT" "geodeticDatum"
## [49] "kingdom" "specificEpithet"
## [51] "recordedBy" "classid"
## [53] "phylum" "species"
## [55] "coordinatePrecision" "subphylum"
## [57] "subclass" "family"
## [59] "kingdomid" "node_id"
## [61] "flags" "sss"
## [63] "shoredistance" "sst"
## [65] "bathymetry" "associatedReferences"
## [67] "type" "taxonRemarks"
## [69] "recordNumber" "georeferencedDate"
## [71] "verbatimEventDate" "collectionCode"
## [73] "license" "dateIdentified"
## [75] "ownerInstitutionCode" "bibliographicCitation"
## [77] "scientificNameAuthorship" "coordinateUncertaintyInMeters"
## [79] "institutionCode" "identificationRemarks"
## [81] "nomenclaturalCode" "datasetName"
## [83] "taxonomicStatus" "waterBody"
## [85] "datasetID" "occurrenceRemarks"
## [87] "organismQuantity" "locality"
## [89] "organismQuantityType" "year"
## [91] "maximumDepthInMeters" "verbatimLatitude"
## [93] "organismID" "samplingProtocol"
## [95] "minimumDepthInMeters" "verbatimLongitude"
## [97] "depth" "stateProvince"
## [99] "sex" "references"
## [101] "fieldNotes" "day"
## [103] "month" "rightsHolder"
## [105] "eventTime" "associatedMedia"
## [107] "taxonID" "countryCode"
## [109] "lifeStage" "locationID"
## [111] "fieldNumber" "identifiedBy"
## [113] "otherCatalogNumbers" "organismRemarks"
## [115] "verbatimLocality" "identificationID"
## [117] "informationWithheld" "accessRights"
## [119] "eventRemarks" "dynamicProperties"
## [121] "georeferenceRemarks" "minimumElevationInMeters"
## [123] "maximumElevationInMeters" "language"
## [125] "eventID" "startDayOfYear"
## [127] "parentEventID"2.1.1 Problemas encontrados
Os dados disponíveis em repositórios abertos são repletos de dados oriundos de diversas fontes. Algumas vezes os coletores não conseguem capturar as informações de forma completa ou ocorrem alguns erros inerentes a coleta ou inserção destes dados nos repositórios.
Devido a elevada quantidade de informações se faz necessária a seleção das variáveis que possam ser utilizadas para a análise. Nesse sentido, foram selecionadas as seguintes variáveis: scientificName, decimalLatitude, decimalLongitude, bathymetry, flags, waterBody, basisOfRecord, occurrenceStatus, rightsHolder,datasetName, recordedBy, depth, locality, date_year, individualCount, year, sex.
##Selecionar variáveis
franca_obis1 <- franca_obis %>%
dplyr::select(scientificName, decimalLatitude, decimalLongitude, bathymetry,
flags, waterBody, basisOfRecord, occurrenceStatus, rightsHolder,
datasetName, recordedBy, depth, locality, date_year, individualCount, sex) %>%
distinct()Desse modo, os dados foram reduzidos a 12.136 observações dentre as 17 variáveis selecionadas. A fim de manter-se a qualidade das informações, precisamos verificar os possiveis problemas com os dados. Importante observar que neste repositório os problemas reportados são denominados de flags.
# check problemas reportados (flags)
franca_obis1 %>%
distinct(flags)## # A tibble: 13 x 1
## flags
## <chr>
## 1 no_depth
## 2 NO_DEPTH
## 3 DEPTH_EXCEEDS_BATH
## 4 NO_DEPTH,ON_LAND
## 5 <NA>
## 6 no_depth,on_land
## 7 ON_LAND
## 8 on_land
## 9 ON_LAND,DEPTH_EXCEEDS_BATH
## 10 on_land,no_depth
## 11 ON_LAND,NO_DEPTH
## 12 depth_exceeds_bath,on_land
## 13 on_land,depth_exceeds_bath#check NA em datasetName
franca_obis1 %>%
filter(!flags %in% c("ON_LAND,NO_DEPTH", "no_depth,on_land", "depth_exceeds_bath,on_land", "on_land,no_depth", "on_land", "on_land,depth_exceeds_bath", "ON_LAND", "ON_LAND,DEPTH_EXCEEDS_BATH"),
is.na(datasetName)) %>%
distinct(waterBody)## # A tibble: 12 x 1
## waterBody
## <chr>
## 1 <NA>
## 2 South Atlantic Ocean
## 3 Southern Ocean
## 4 Indian
## 5 Atlantic
## 6 Sub-Antarctic waters
## 7 Antartic waters
## 8 Patagonian shelf
## 9 South Pacific Ocean
## 10 Atlantic Ocean
## 11 Indian Ocean
## 12 San Jorge, GulfAs flags foram utilizadas para filtrar ocorrências da nossa espécie em terra e remover do nosso conjunto de dados os dataset que não apresentaram informações (NA). Além disso, aplicamos um filtro para remover a duplicidade de ocorrências e plotamos um gráfico verificando uma linha do tempo dos relatos da baleia franca austral:
#depth ok
franca_obis1 %>%
filter(!flags %in% c("ON_LAND,NO_DEPTH", "no_depth,on_land", "depth_exceeds_bath,on_land", "on_land,no_depth", "on_land", "on_land,depth_exceeds_bath", "ON_LAND", "ON_LAND,DEPTH_EXCEEDS_BATH"),
!is.na(datasetName),
!waterBody %in% c("world","Global,French EEZ")) %>%
ggplot(aes(x = date_year, fill = waterBody)) +
geom_histogram() 
# checar niveis
franca_obis1 %>%
filter(!flags %in% c("ON_LAND,NO_DEPTH","no_depth,on_land","depth_exceeds_bath,on_land","on_land,no_depth", "on_land", "on_land,depth_exceeds_bath", "ON_LAND", "ON_LAND,DEPTH_EXCEEDS_BATH"),
!is.na(datasetName),
!waterBody %in% c("world","Global,French EEZ")) %>%
lapply(., unique)## $scientificName
## [1] "Eubalaena australis"
##
## $decimalLatitude
## [1] -44.64320 -51.68076 -50.48730 -40.88212 -50.55630 -47.13330 -42.62050
## [8] -50.48720 -42.73579 -50.49410 -50.48740 -46.66670 -50.51240 -40.81177
## [15] -50.50480 -50.49510 -40.86700 -36.50000 -50.50350 -40.85157 -40.89182
## [22] -50.48900 -54.83646 -50.48800 -50.49870 -40.86750 -50.54430 -35.50000
## [29] -50.53960 -41.33330 -50.49720 -40.88977 -50.55290 -41.28450 -40.79692
## [36] -50.55940 -45.90000 -50.51050 -50.52130 -50.49960 -42.68367 -50.55480
## [43] -64.19000 -50.53310 -40.83478 -50.49380 -50.50260 -50.48960 -40.86787
## [50] -50.48410 -50.48750 -50.55790 -50.50940 -50.52000 -40.85000 -44.66930
## [57] -40.79895 -50.52400 -53.85542 -39.38330 -54.05698 -54.07299 -50.50820
## [64] -42.58362 -50.55590 -50.48690 -50.51030 -55.10000 -50.49600 -50.49120
## [71] -40.87797 -40.83487 -51.46651 -50.49110 -50.52710 -50.49020 -46.98330
## [78] -50.51340 -50.50410 -40.87440 -40.98935 -50.48930 -39.06670 -50.52450
## [85] -50.53120 -39.07270 -50.48950 -50.49350 -50.48780 -50.48620 -40.82203
## [92] -50.52650 -50.48990 -40.81017 -50.53260 -50.54690 -50.49050 -50.48920
## [99] -50.55330 -42.00000 -45.89950 -52.36076 -39.74750 -50.51730 -50.49840
## [106] -50.54260 -50.53170 -53.70000 -50.52300 -40.86708 -42.43810 -46.90000
## [113] -50.50730 -37.47480 -50.52890 -40.85007 -37.60200 -50.51780 -50.55340
## [120] -50.50870 -50.55440 -40.80258 -46.40000 -40.77780 -50.53500 -42.40000
## [127] -53.08000 -50.48600 -50.52100 -50.52880 -50.55410 -50.50270 -50.52820
## [134] -50.55170 -50.52080 -40.85177 -34.02305 -50.55270 -50.54300 -50.49680
## [141] -50.48630 -50.52220 -50.55300 -50.52340 -50.55420 -50.51550 -50.51160
## [148] -42.60000 -42.57468 -50.48650 -54.02000 -41.36670 -40.81887 -50.49070
## [155] -50.50300 -50.50330 -50.55620 -50.51670 -53.17382 -40.87150 -40.81218
## [162] -50.50880 -40.77670 -50.52560 -50.51080 -41.34418 -40.80807 -50.48790
## [169] -39.07350 -20.62000 -40.80808 -42.34000 -62.90000 -54.07250 -46.91560
## [176] -40.84163 -51.43000 -39.08330 -50.51750 -50.52530 -50.49560 -50.52330
## [183] -40.84357 -50.48710 -50.54070 -40.84110 -40.82373 -40.81615 -14.76130
## [190] -34.03667 -41.31365 -50.55380 -50.51220 -54.55000 -41.20490 -50.55570
## [197] -38.52720 -40.82253 -50.52360 -38.70000 -50.49080 -50.50970 -41.28330
## [204] -50.55880 -40.84185 -46.61450 -43.58250 -50.50750 -54.20000 -50.53670
## [211] -51.66574 -50.48810 -42.58465 -50.50200 -50.50950 -40.89457 -50.55360
## [218] -50.52040 -53.54880 -40.82922 -46.30000 -50.53000 -50.54900 -39.10000
## [225] -50.48830 -50.55470 -62.11500 -54.00860 -50.49040 -40.80815 -50.50570
## [232] -50.50420 -40.84040 -41.26833 -42.61267 -50.54480 -40.85820 -41.40000
## [239] -39.00000 -53.38298 -40.82065 -40.68550 -55.06000 -39.42340 -45.65000
## [246] -50.55230 -42.70400 -50.54460 -50.55700 -50.55710 -50.52490 -50.55810
## [253] -50.49540 -50.51660 -42.63852 -45.76670 -39.05350 -46.61360 -50.52250
## [260] -50.52910 -40.79612 -37.93330 -42.66779 -50.48890 -50.52150 -50.48570
## [267] -50.56010 -35.80000 -41.34560 -40.86123 -41.30000 -35.60650 -50.49780
## [274] -50.52190 -50.52610 -45.26670 -40.82845 -45.63600 -46.56670 -17.94000
## [281] -50.53730 -61.17000 -45.82110 -41.21870 -50.49010 -42.76883 -40.82303
## [288] -50.49330 -50.54720 -38.88330 -50.51790 -50.49200 -52.39043 -50.54010
## [295] -55.12000 -50.55200 -62.94586 -40.83907 -52.43000 -39.07650 -50.55000
## [302] -50.55500 -39.03330 -50.52090 -34.63462 -40.30570 -51.67955 -50.55560
## [309] -46.59260 -40.87618 -37.93480 -50.55240 -40.85178 -42.76000 -40.84140
## [316] -55.77000 -46.59360 -40.86023 -40.79428 -40.83153 -50.53830 -45.79620
## [323] -50.55660 -45.63330 -50.51950 -50.53150 -50.48870 -50.50310 -45.41670
## [330] -50.48680 -41.30747 -40.88667 -54.01584 -35.87000 -40.82393 -46.92770
## [337] -46.87540 -40.83330 -50.52180 -40.81978 -37.94790 -50.51390 -50.52510
## [344] -45.35660 -39.90000 -50.54550 -50.52780 -50.52850 -47.17080 -50.52830
## [351] -43.96670 -50.55530 -50.50510 -40.89790 -40.83020 -50.49570 -50.50900
## [358] -40.83110 -50.50470 -40.82792 -45.95000 -38.98330 -53.40609 -51.67864
## [365] -38.28000 -50.49290 -52.39491 -35.18330 -50.55750 -40.82337 -50.49230
## [372] -40.83725 -50.48840 -50.52550 -50.51190 -54.04974 -50.54960 -50.53760
## [379] -40.81408 -50.52600 -50.55860 -40.81868 -40.86135 -50.55320 -40.85113
## [386] -40.80672 -54.03000 -26.82633 -52.42000 -50.48980 -50.51940 -50.53160
## [393] -42.62144 -40.86080 -45.79330 -39.15610 -50.54200 -40.88613 -50.52070
## [400] -53.36049 -40.83923 -40.84483 -50.55220 -50.56720 -40.81522 -46.90400
## [407] -41.24070 -50.55010 -40.86202 -50.54770 -45.91670 -50.50910 -53.41291
## [414] -40.71990 -34.54090 -50.51980 -40.82305 -35.86230 -50.54250 -40.84083
## [421] -50.48770 -50.50400 -41.28474 -53.51117 -37.63500 -50.54980 -47.01670
## [428] -50.54050 -50.48530 -63.32610 -40.82597 -50.50690 -50.48500 -37.76000
## [435] -40.80228 -40.81342 -40.83757 -40.79850 -50.55080 -52.40948 -41.34469
## [442] -60.27542 -64.36167 -34.95000 -50.50360 -51.46661 -50.49300 -43.61090
## [449] -50.50450 -50.55580 -40.86972 -50.50230 -40.82015 -28.07464 -40.83828
## [456] -50.48350 -50.50670 -50.55540 -50.51150 -50.53780 -46.92920 -42.73410
## [463] -38.71670 -39.05000 -50.53100 -55.66281 -50.52060 -50.51500 -50.48440
## [470] -50.53800 -45.46480 -51.67991 -46.84580 -35.11680 -40.82150 -51.42980
## [477] -45.47720 -37.66670 -50.53440 -46.89170 -40.81837 -41.27003 -40.79780
## [484] -50.48520 -42.70000 -40.86868 -39.48330 -42.42950 -50.50580 -50.53550
## [491] -40.81258 -40.76283 -50.52680 -40.82180 -40.82400 -41.27000 -50.54530
## [498] -46.36670 -39.06000 -50.54870 -42.80000 -39.12980 -43.00000 -50.50760
## [505] -54.14200 -41.31494 -50.54190 -50.49340 -50.55550 -50.53970 -50.49240
## [512] -55.15000 -37.63330 -40.90820 -50.53340 -41.00516 -52.39074 -61.70062
## [519] -40.82668 -45.76820 -35.93330 -50.53880 -50.50120 -40.90340 -40.84552
## [526] -40.86125 -50.55900 -50.49390 -50.49710 -41.28751 -50.52800 -42.74292
## [533] -42.60111 -50.50800 -50.48370 -40.83892 -50.52200 -45.77080 -43.88330
## [540] -50.53370 -50.51480 -54.03643 -50.51860 -43.80000 -50.52270 -40.82698
## [547] -50.53640 -45.81650 -34.49151 -40.85673 -50.54310 -37.65000 -46.21670
## [554] -45.78330 -25.05153 -51.67930 -50.50490 -50.52480 -50.53400 -43.83330
## [561] -50.51600 -40.85225 -34.15108 -40.90152 -50.55970 -40.83200 -50.49880
## [568] -50.54170 -37.63880 -42.58449 -54.05000 -40.82335 -40.84193 -38.75000
## [575] -50.50210 -50.48660 -50.49640 -46.23440 -55.14859 -40.81888 -53.61125
## [582] -50.55120 -50.53130 -40.84288 -50.55190 -43.53330 -41.59467 -50.50320
## [589] -50.50560 -53.72000 -51.66459 -40.90420 -36.86620 -40.81653 -33.84695
## [596] -50.54580 -42.47260 -50.51630 -36.59940 -50.53930 -50.49320 -50.50140
## [603] -50.48560 -40.85772 -40.85367 -50.53850 -50.52500 -46.65000 -50.48940
## [610] -40.83340 -40.79935 -40.86317 -50.48220 -51.60000 -56.28000 -50.53070
## [617] -50.54280 -40.78243 -50.51400 -50.53410 -39.63330 -50.51280 -50.49690
## [624] -50.55510 -45.83330 -53.52700 -47.20000 -45.75000 -37.60000 -40.85667
## [631] -50.56030 -50.53430 -50.51570 -50.51760 -43.73460 -41.35440 -50.48860
## [638] -50.51820 -50.54520 -46.59040 -50.54710 -41.41670 -40.83703 -50.51680
## [645] -40.80060 -61.70171 -50.53560 -50.52420 -51.67637 -40.80303 -45.86440
## [652] -34.42389 -40.86110 -54.29589 -40.83555 -40.85163 -45.77160 -40.78380
## [659] -46.78100 -47.19530 -54.76356 -40.82017 -34.50000 -50.54110 -41.17220
## [666] -40.85780 -50.54590 -50.50630 -50.49650 -40.84262 -42.76253 -46.70000
## [673] -42.59477 -50.49310 -50.50380 -54.02070 -42.62781 -60.37715 -41.28744
## [680] -37.57040 -46.58330 -50.50650 -54.80000 -40.82133 -50.55820 -53.90000
## [687] -50.53900 -50.51430 -50.51270 -41.35020 -50.55600 -40.86455 -46.93330
## [694] -50.55390 -39.23000 -51.67762 -40.83278 -50.51540 -50.49170 -50.52290
## [701] -50.49660 -39.45000 -43.56670 -51.65392 -46.50780 -34.18000 -50.53210
## [708] -50.50240 -50.51090 -40.83548 -50.51690 -40.80203 -40.90092 -40.81633
## [715] -39.22000 -40.90535 -40.85598 -40.85543 -34.49730 -50.48290 -50.55160
## [722] -43.55000 -40.81497 -55.77374 -41.28256 -50.52460 -42.48330 -46.61650
## [729] -50.52790 -50.55460 -64.33515 -40.79902 -50.53190 -40.82170 -38.36670
## [736] -39.07220 -40.82717 -51.66078 -50.55130 -50.53520 -64.14277 -34.15611
## [743] -40.86448 -40.89237 -45.71670 -40.79343 -50.51450 -50.51330 -51.67101
## [750] -52.55004 -41.26420 -50.55250 -50.49820
##
## $decimalLongitude
## [1] 167.90260 -57.76472 166.27840 -64.78952 166.20320 168.11670 -64.26066
## [8] 166.28140 -64.41301 166.32710 166.31590 169.11670 166.18520 -65.04812
## [15] 166.33660 -64.92707 174.75000 166.28210 -64.99763 -64.84447 166.33210
## [22] -35.81090 166.32090 -65.03545 166.21450 174.73330 166.21820 174.25000
## [29] 166.32570 -65.00248 166.19540 174.78691 -65.03593 166.18500 170.68330
## [36] 166.19750 166.19890 166.32540 -64.33409 166.19560 -62.57000 166.23570
## [43] -65.06045 166.26640 166.28120 166.26270 -64.99687 166.30460 166.27030
## [50] 166.19300 166.26290 173.03330 166.30040 167.92490 -64.97138 166.26530
## [57] -38.44239 176.90000 -37.42276 -36.74120 166.30000 166.32010 -64.34795
## [64] 166.19910 166.29590 166.29510 -30.74000 166.32250 -64.72667 -64.95143
## [71] -57.83519 166.33140 166.26470 166.29790 166.32220 166.25870 166.32160
## [78] -64.82190 174.94129 166.32470 174.00000 166.28580 166.25420 177.85290
## [85] 166.32100 166.33350 166.27630 166.29090 -64.97692 166.22490 166.32450
## [92] -65.07238 166.23120 166.21790 166.24520 166.32310 166.27320 166.21890
## [99] 166.32740 171.35000 170.64480 -68.38650 177.02300 166.27450 166.25990
## [106] 166.21630 166.24260 -41.83600 166.22940 -64.93613 171.18420 166.28850
## [113] 168.16670 166.29770 166.29400 177.21380 166.24920 -65.09155 178.34600
## [120] 166.24150 166.19700 166.30310 166.19020 -64.98815 172.18330 -65.00090
## [127] 166.21490 173.70000 -46.30000 166.31080 166.32500 166.23430 166.26230
## [134] 166.19160 166.24000 166.21470 166.27060 -64.99883 18.28611 166.21660
## [141] 166.22030 166.32990 166.26700 166.31710 166.20230 166.20810 166.19860
## [148] 166.20820 166.29450 -64.60000 166.19050 -64.32100 166.31440 -36.48000
## [155] 174.71670 -65.06187 166.32440 166.25320 166.27880 166.21060 166.28460
## [162] -44.55735 -64.93420 -65.07222 166.30910 166.25080 -64.92062 166.24180
## [169] 166.30100 174.81403 -65.06313 166.28090 166.29760 166.29600 166.31560
## [176] 177.43330 -38.08000 -65.06493 -64.50000 -64.16000 166.18490 166.28930
## [183] 166.24650 -60.40000 -37.98330 168.14320 166.31890 -64.82842 166.19410
## [190] -40.18000 177.96670 166.19450 166.32800 166.26510 -65.06010 166.30850
## [197] 166.24280 -65.03228 -64.95930 -64.98865 -38.97340 18.30278 174.80610
## [204] 166.20010 166.26200 166.23310 -35.88330 174.36780 166.19920 178.31260
## [211] -65.06985 166.29490 166.19710 178.10000 166.27560 174.80000 166.19030
## [218] -64.76548 168.36920 172.77990 166.18320 -36.00000 -57.77297 166.32280
## [225] -64.32117 166.29430 166.29730 -64.85325 166.27650 -42.04370 -65.04310
## [232] 167.61670 166.26020 166.26600 166.22740 177.28330 166.31260 166.28960
## [239] 166.18950 -57.93000 -37.35193 166.26500 -65.05293 166.29120 166.18620
## [246] 166.32270 166.23920 -64.95945 174.79553 -63.26450 166.22140 -65.03175
## [253] 175.06670 177.86670 -49.92000 -43.46257 166.22630 -64.99838 -58.01557
## [260] -31.28000 176.89120 170.66430 166.20090 -63.31467 166.23620 166.19490
## [267] 166.19660 166.30640 166.20960 166.22560 166.18890 166.32860 166.26160
## [274] 166.19690 -64.92702 170.73330 177.68100 168.37920 166.25850 -64.99747
## [281] 177.03330 -64.97735 -64.94887 166.32480 166.19650 166.33120 166.32360
## [288] 166.18340 174.45000 174.19670 173.96670 -64.94130 174.53830 166.33050
## [295] 166.22850 166.24070 166.83330 -64.97827 170.79300 169.50000 166.29710
## [302] -38.88000 166.21550 -54.62000 170.62930 174.29610 166.32370 -63.33683
## [309] -64.99880 166.29460 166.31040 166.32660 166.22130 174.51670 166.19900
## [316] 166.22950 166.33390 -68.41346 -30.58000 166.19620 -60.35408 -64.97452
## [323] -40.85000 177.38330 166.21370 166.18800 174.10000 166.29830 19.39756
## [330] 176.68380 166.24400 -57.77169 166.20460 168.35070 -64.79548 177.00670
## [337] -65.06925 166.28990 -65.02000 166.31010 -64.93562 166.27910 -28.32000
## [344] 168.34230 -65.12023 -65.00223 -65.06955 166.24960 170.70140 173.71670
## [351] 166.18740 170.66670 166.24800 166.22390 166.32770 166.28230 170.83990
## [358] 166.28550 174.81343 -64.85432 -38.12882 174.50000 -65.02983 168.14770
## [365] 168.13780 174.90000 166.25770 -65.03177 177.02440 166.19290 166.22700
## [372] 170.83330 177.26670 166.22290 166.25330 167.67550 166.24640 166.30650
## [379] 166.18480 166.21410 168.75000 166.26970 166.20200 166.26380 -64.87388
## [386] -64.92260 166.32750 166.31170 -64.78880 166.28270 -65.08600 170.55000
## [393] 173.98330 -44.68447 -57.75064 166.19500 -49.43000 166.26820 -68.41556
## [400] 166.19380 166.21580 174.20000 166.19340 -65.06790 166.32590 -65.08577
## [407] 166.29340 166.22910 166.29690 -37.25717 166.21280 166.20800 -65.06958
## [414] 166.27400 166.22480 166.32620 166.25510 166.23490 166.19110 -65.05173
## [421] -64.76328 -64.96407 166.26930 -64.92302 -38.60000 32.89217 -41.03000
## [428] 166.33420 166.22600 -64.23586 -64.81332 170.71670 177.81480 166.23760
## [435] 166.24460 -64.93383 -37.89648 -65.00992 -65.06088 166.25710 166.30160
## [442] -64.97188 166.30090 166.18410 168.14670 166.22250 166.18640 166.22350
## [449] 166.20170 -65.09158 166.23590 166.21350 -37.27575 172.69820 19.35516
## [456] -65.07305 166.20440 166.27160 174.51880 166.22180 -65.05528 166.19200
## [463] 166.27860 174.79106 -42.25663 176.20600 166.21120 166.27720 168.23330
## [470] 166.22890 166.28870 -61.00000 -64.76375 166.28240 166.18050 166.31350
## [477] 166.32780 166.28820 176.55000 -65.04912 -65.07040 -65.04128 -65.05323
## [484] -68.41315 166.20630 166.32200 174.78497 -45.26098 -61.87588 173.50000
## [491] 166.27660 -57.83537 166.26710 166.32840 172.81470 166.19420 -64.91117
## [498] 166.32230 166.28320 -65.03098 -48.62469 -65.04918 166.27870 166.18560
## [505] 166.27620 166.33690 166.20510 166.29860 166.24590 167.98090 -65.02722
## [512] 178.08330 174.03330 -38.03956 166.20770 166.24160 166.20620 166.29520
## [519] 166.31580 170.75000 166.25160 167.16040 -57.72158 168.10040 174.00230
## [526] -64.97153 -57.86239 170.83530 177.20000 166.23450 168.13380 -65.08943
## [533] 174.79232 -64.94898 166.32550 -65.09212 176.93330 166.30890 171.19720
## [540] 166.27360 166.21690 -65.07090 -65.01097 166.22610 166.20270 -65.01183
## [547] 177.83330 -64.96797 174.84000 166.23680 167.90000 177.93000 166.23370
## [554] -64.70000 -64.00000 166.27380 -36.56770 166.31960 174.80916 166.22240
## [561] 166.21480 166.32340 166.19530 166.21780 -30.09000 166.22660 178.45000
## [568] -64.79372 166.25750 174.92390 -68.41257 -40.71237 -65.06898 170.72820
## [575] 170.51670 166.26250 -64.93018 166.30360 166.32290 -65.06003 -64.94132
## [582] 166.18220 166.32870 166.32720 166.26080 174.79381 166.30280 -64.42623
## [589] -64.29028 166.27330 166.32420 166.30220 166.18940 166.30570 170.71580
## [596] 166.30530 166.20110 172.95530 166.26260 -36.80568 166.27700 173.75000
## [603] 166.26920 -65.04588 166.24740 166.21840 170.64470 19.33415 -64.86378
## [610] 166.22160 166.28570 176.30000 167.50000 166.22750 153.09477 -57.79563
## [617] 166.24230 166.32190 166.27230 166.20040 166.23510 172.70000 166.28170
## [624] 166.21850 -64.94750 18.43988 166.29940 166.27110 -64.84370 166.20600
## [631] 166.18780 -64.76157 166.24040 166.25430 176.16900 -64.31319 166.27750
## [638] -38.32000 -64.79250 166.29240 -65.07698 174.30000 166.27990 166.25200
## [645] 166.31320 166.32760 167.01440 166.27780 -65.91213 -64.95543 -41.84692
## [652] -65.07967 166.20940 172.76670 -61.44433 166.27000 166.27310 -36.42000
## [659] 166.30940 166.31070 -57.75957 -64.96982 166.29170 175.02940 -65.00407
## [666] 18.41909 166.23810 166.33160 166.25250 171.17550 166.19990 174.81080
## [673] 166.23410 166.22320 166.33040 166.24010 -65.00852 -64.73540 166.20290
## [680] 166.23190 166.23750 166.32110 -65.05832 -64.95422 -65.07693 166.29220
## [687] 166.29190 -57.80000 -26.33000 166.22220 166.19350 -64.99558 166.19480
## [694] 177.01670 166.29070 166.25980 166.20720 -42.00900 166.32670 167.66670
## [701] 166.31900 176.38330 -64.79272 166.28540 166.25790 173.11120 174.77810
## [708] 166.23480 168.34620 166.22840 174.86670 -65.05398 166.28510 166.21330
## [715] 166.30700 -64.97872 -51.57980 166.21750 166.25050 -57.74157 166.32560
## [722] 166.21360 -65.00145 170.74710 19.24299 -64.85825 -36.43341 -64.97742
## [729] -64.76245 166.31780 170.72470 166.21610 -64.95178 166.19260 168.00410
## [736] 167.68700 -35.79208 -65.07670 19.23000 174.18970 166.27900 -65.06002
## [743] 166.31990 166.18290 166.23790 -64.76392 166.28840 -65.00000 168.33330
## [750] 169.08330 166.27480 -64.26350 166.27940 -64.23767 -51.85442 174.79290
## [757] 178.30260 168.34650 166.28760 -35.76000 -65.08342 166.18160 166.19880
## [764] -38.00000 166.20570 166.21130 166.21640 166.28880 166.23980 174.10440
## [771] 166.20650 -64.91182 166.30130 166.30670 168.05000 -49.85000 -57.77492
## [778] 166.32460 -64.93835 166.27410 166.26870 166.26040 176.88330 -57.80163
## [785] 168.25000 22.16000 166.22770 166.28330 -64.99802 166.30950 -64.73042
## [792] -65.03388 -64.81280 -65.08020 -49.78000 -64.91418 166.32400 -64.94102
## [799] -64.97242 19.35240 166.30840 166.27300 166.19770 166.23150 -64.92283
## [806] -64.56223 174.79022 166.23340 166.22620 174.05000 166.23600 173.56670
## [813] 168.36330 166.22830 -61.79398 -65.05188 166.25590 166.25620 166.28640
## [820] 166.32150 178.31670 177.79820 166.30800 166.20400 -65.06132 166.23030
## [827] -51.66078 166.21990 166.22650 166.20210 -60.92973 18.43805 -64.92762
## [834] 166.18650 -64.91282 170.61670 -64.98473 166.25650 166.29920 166.26240
## [841] -57.74018 -50.21689 174.78919 166.21810 166.19800 166.21090 166.24250
##
## $bathymetry
## [1] -236.00 -3.00 -9.00 7.00 -5.00 38.00 155.00 20.00 -6.00
## [10] 23.00 -1.00 8.00 -2.00 27.00 2.00 11.00 6.00 26.00
## [19] 28.00 128.00 18.00 120.00 21.00 74.00 9.00 -10.00 14.00
## [28] -52.00 43.00 127.00 24.00 5.00 17.00 -256.00 15.00 143.00
## [37] 57.00 114.00 -14.00 87.00 5915.00 10.00 -12.00 106.00 -4.00
## [46] 25.00 -8.00 -16.00 51.00 1.00 133.00 3.00 4.00 245.00
## [55] 13.00 12.00 -38.00 1465.00 -18.00 1675.00 78.00 138.00 16.00
## [64] 182.00 81.00 2067.00 54.00 126.00 45.00 676.00 131.00 3739.00
## [73] 31.00 79.00 19.00 101.00 197.00 35.00 22.00 118.00 341.00
## [82] 41.00 76.00 5286.00 1363.00 93.00 5415.00 -23.00 42.00 34.00
## [91] 68.00 147.00 30.00 301.00 -33.00 72.00 5981.00 836.00 3770.00
## [100] 32.00 1515.00 65.00 29.00 -24.00 48.00 -29.00 327.00 -21.00
## [109] 90.00 795.00 5211.00 -27.00 52.00 180.00 3763.00 2565.00 1182.00
## [118] 190.00 484.00 -76.00 3816.00 549.00 -34.00 -59.00 -13.00 3614.00
## [127] 259.00 156.00 -15.00 111.00 69.00 70.00 5521.00 60.00 3606.00
## [136] 71.00 -28.00 154.00 55.00 247.00 94.00 17.34 -47.00 162.00
## [145] 598.00 134.00 413.00 4120.00 153.00 -53.00 -50.00 2650.00 144.00
## [154] -22.00 450.00 64.00 123.00 5375.00 36.00 -26.00 5380.00 3781.00
## [163] 92.00 752.00 927.00 2242.00 255.00 3534.00
##
## $flags
## [1] "DEPTH_EXCEEDS_BATH" "no_depth" NA
## [4] "NO_DEPTH"
##
## $waterBody
## [1] "Pacific Ocean"
## [2] "South Atlantic Ocean"
## [3] "Argentina,Patagonia,Bahía San Antonio"
## [4] "Southern Ocean"
## [5] NA
## [6] "South Pacific Ocean"
## [7] "Mozambique Channel"
## [8] "Coral Sea"
## [9] "Indian Ocean"
##
## $basisOfRecord
## [1] "HumanObservation"
##
## $occurrenceStatus
## [1] "present" NA
##
## $rightsHolder
## [1] NA "Sue Luxton"
## [3] "Jean Pierre Orduña R." "Santiago Imberti"
## [5] "Hans Verdaat" "nicolemiller"
## [7] "Vicki Beaver" "Sara Jenner"
## [9] "Adrian Boyle" "Sergey Subbotin"
## [11] "Jamie Coleman" "Andy McKay"
## [13] "Tom Barcley" "Daniela Abras"
## [15] "Cees Tineke" "Frank Tetreault"
## [17] "Conor Ryan" "Pierre Tellier"
## [19] "Sonia Pazos de Diego" "Cristián Rizzi"
## [21] "Marian Herz" "Carolyn Peterson"
## [23] "Ecosul Turismo" "Javier Cotin"
## [25] "Rob Creek" "Phillip Hunter"
## [27] "Leon Perrie" "Tobias Brehm"
## [29] "Alain Bidart" "Rémi Bigonneau"
## [31] "Renata Sousa-Lima" "Frank Fish"
## [33] "Martin Anstee" "Dr. med Hartmut Bombosch"
## [35] "Claude Joiris" "thankyou"
## [37] "Ella Potts" "Stefan Bernhard"
## [39] "Mark" "Ricardo Matus"
## [41] "Angie Gullan" "Paul McKinley"
## [43] "Troels Jacobsen" "Povl Abrahamsen"
## [45] "Fanny" "Marina Rehder"
## [47] "Annette Bombosch" "Nikki"
## [49] "Dan Ross" "Peter Geraerts"
## [51] "Steph & Oli Prince" "rasshamra"
## [53] "benknight" "Tim Park"
## [55] "Ran Dembo" "John White"
## [57] "Mark Andrew Cornish" "Charles Booysen"
## [59] "Christian Wegener" "Christian Engelke"
## [61] "Andrew Stanworth" "Ana"
## [63] "Joanna Lim" "Ken Finlay"
## [65] "Alison Ballance" "Ted Cheeseman"
## [67] "Jim Wilson" "Southern Right Charters"
## [69] "Siobhan Leachman" "Pamela Le Noury"
## [71] "Dewald van Breda" "Marina Costa"
## [73] "Gil Elimor" "Ton Knijnenburg"
## [75] "wild_wind"
##
## $datasetName
## [1] "Sightings of southern right whales around mainland New Zealand 1976-2002"
## [2] "Happywhale - Southern Right Whale in South Atlantic Ocean"
## [3] "Southern right whales wintering in the Auckland Islands 1996-1998"
## [4] "Marybio Foundation marine mammal aerial sightings in Bahia San Antonio, Patagonia 2008-2010"
## [5] "Marybio Foundation marine mammal shipboard sightings in Bahia San Antonio, Patagonia 2008-2010"
## [6] "iNaturalist research-grade observations"
## [7] "Happywhale - Southern Right Whale in Southern Ocean"
## [8] "ANT_29-4"
## [9] "Happywhale - Southern Right Whale in South Pacific Ocean"
## [10] "UK Royal Navy Marine Mammal Observations"
## [11] "MBIS Marine Fauna and Flora observations around New Zealand"
## [12] "Happywhale - Southern Right Whale in Indian Ocean"
##
## $recordedBy
## [1] "Lusseau & Slooten 2002"
## [2] "Sue Luxton"
## [3] NA
## [4] "Hilary Squires"
## [5] "Jean Pierre Orduña R."
## [6] "Santiago Imberti"
## [7] "Nancy Gee, DOC"
## [8] "Thelma Wilson, DOC"
## [9] "Hans Verdaat"
## [10] "Cawthorn 1990"
## [11] "Zoe Battersby, Dolphin Watch Marlborough"
## [12] "nicolemiller"
## [13] "Karen Baird, Graeme Loh, Richard Nichol, DOC"
## [14] "Vicki Beaver"
## [15] "Hugh Mytton, Totaranui Camp Manager, Nelson paper"
## [16] "Mary Mayes, Whirinaki; Hans Rook, DOC"
## [17] "Sara Jenner"
## [18] "Adrian Boyle"
## [19] "Jamie Coleman"
## [20] "Mussel farmers reported to DOC; Southland Times"
## [21] "Andy McKay"
## [22] "Barry Hartley"
## [23] "Malcolm Smith, DOC"
## [24] "Reported to D. Neal, DOC"
## [25] "Eduardo Secchi, University of Otago"
## [26] "Hans Rook, DOC"
## [27] "Tom Barcley"
## [28] "Phil Lowe, Dolphin Adventure Tours"
## [29] "Brent Beaven, DOC"
## [30] "Kim Westerkov"
## [31] "Daily Post"
## [32] "Richard Win, Seiryo Maru 12"
## [33] "B. Todd in Duffy & Brown 1994"
## [34] "Daniela Abras"
## [35] "Cees Tineke"
## [36] "Frank Tetreault"
## [37] "Bruce Dix, DOC"
## [38] "Pierre Tellier"
## [39] "Sonia Pazos de Diego"
## [40] "Marian Herz"
## [41] "Carolyn Peterson"
## [42] "P. Dobbins, P. Lowan, P. Crouchly"
## [43] "reported to Helen Jonas, DOC"
## [44] "Ecosul Turismo"
## [45] "Conor Ryan"
## [46] "Boyd McGregor, local charter operator"
## [47] "Ms Storm Dunn"
## [48] "The Evening Post"
## [49] "Southland Conservancy"
## [50] "Jim Lilley, Marine Watch"
## [51] "Javier Cotin"
## [52] "Rob Creek"
## [53] "Southland Times"
## [54] "Andrew Glaser, DOC"
## [55] "Phillip Hunter"
## [56] "Leon Perrie"
## [57] "Tobias Brehm"
## [58] "Roger Bunckenberg, Wellington Flight Centre"
## [59] "Alain Bidart"
## [60] "Rémi Bigonneau"
## [61] "John Adams, DOC"
## [62] "DOC sighting report"
## [63] "Reported to Monarch Cruises"
## [64] "Southern Air"
## [65] "Rosemary Tully"
## [66] "Ingrid Visser"
## [67] "F. Robsonís day book, reported by C. Duffy, DOC"
## [68] "Bryan Williams, DOC"
## [69] "Jenny Burling"
## [70] "Bob Walker, Renown"
## [71] "Tour operator Mary Sutherland"
## [72] "Renata Sousa-Lima"
## [73] "Otago Daily Times, Monarch Cruises"
## [74] "reported to Malcolm Smith, DOC"
## [75] "Frank Fish"
## [76] "Carol Sciascia"
## [77] "Martin Anstee"
## [78] "Reported to DOC"
## [79] "Coastguard report forwarded by Rosemary Tully, Marlborough Dolphin Watch"
## [80] "Dr. med Hartmut Bombosch"
## [81] "Claude Joiris"
## [82] "Richard Oliver, Monarch Cruises"
## [83] "Barbara Todd"
## [84] "Otago Daily Times"
## [85] "Dave Houston"
## [86] "thankyou"
## [87] "Ella Potts"
## [88] "Patrick Kavanagh"
## [89] "Thalassa Kawachi aboard Rilyara"
## [90] "Gary Neave"
## [91] "Brent Trolle, DOC"
## [92] "Liz Baynes, Tim Shaw, Murray Smith"
## [93] "D. Nelson, DOC"
## [94] "Stefan Bernhard"
## [95] "Mark"
## [96] "Ricardo Matus"
## [97] "Andrew Ryding, University of Auckland"
## [98] "Angie Gullan"
## [99] "Monarch Cruises"
## [100] "Jason Braid on fishing vessel"
## [101] "Sharon Pasco, DOC"
## [102] "G. Loh"
## [103] "Simon Hall, DOC"
## [104] "Paul McKinley"
## [105] "Bill Cash, reported in Duffy & Brown 1994"
## [106] "M. Peterson"
## [107] "Troels Jacobsen"
## [108] "Paul Keyes, Bay of Plenty Polytech"
## [109] "Peter Simpson, DOC"
## [110] "Fanny"
## [111] "George Wallbank"
## [112] "Rob Suisted, DOC; Dennis Buurman"
## [113] "Marina Rehder"
## [114] "Annette Bombosch"
## [115] "Oakura Daily News, from Bryan Williams, DOC"
## [116] "Fisher reported to Monarch Cruises"
## [117] "Nikki"
## [118] "Graham Clifford"
## [119] "John Baker, MV Ma Cheri"
## [120] "Dan Ross"
## [121] "GES, Trevor Johnston"
## [122] "Helen Jonas, DOC"
## [123] "Malcom Smith, DOC"
## [124] "Jamie Quirk, DOC"
## [125] "Peter Geraerts"
## [126] "Steph & Oli Prince"
## [127] "rasshamra"
## [128] "commercial fisher reported to Jamie Quirk, DOC Gisborne"
## [129] "benknight"
## [130] "Dean Nelson, DOC"
## [131] "Carol Turner, Papatoetoe"
## [132] "Tim Park"
## [133] "Ran Dembo"
## [134] "G. Loh, DOC"
## [135] "Diane Clement, Otago University"
## [136] "Simon Childerhouse, DOC"
## [137] "Graeme Loh, DOC"
## [138] "Andy Cox, DOC"
## [139] "S. Hellyer, DOC"
## [140] "Mark Andrew Cornish"
## [141] "Charles Booysen"
## [142] "Bay of Plenty Times"
## [143] "Reported to Bryan Williams, DOC"
## [144] "Sam Dufresne, Otago University"
## [145] "Christian Wegener"
## [146] "Don Neal, Greymouth Evening Star"
## [147] "Scott Wyatt"
## [148] "Flipper Robsonís diary"
## [149] "Karen Baird, Chris Lalas, DOC"
## [150] "Christian Engelke"
## [151] "Alan Tennison"
## [152] "Signal station, reported to Monarch Cruises"
## [153] "Marco Zeeman"
## [154] "Andrew Stanworth"
## [155] "George Lay, tour operator"
## [156] "The Press, The Star (Christchurch)"
## [157] "Ana"
## [158] "Sandra McGrouther"
## [159] "R. Shaw, Breaksea Girl"
## [160] "Dave Waters"
## [161] "Mike Aviss, DOC"
## [162] "Joanna Lim"
## [163] "Zoe Battersby, Dolphin Watch Marlborough; Bill Cash, DOC"
## [164] "Bob Hawkes, Mana Charters"
## [165] "Alison Balance"
## [166] "Alison Ballance"
## [167] "nephew of Hal Hovell, DOC"
## [168] "TVNZ"
## [169] "Ted Cheeseman"
## [170] "Jim Wilson"
## [171] "Anonymous report to DOC"
## [172] "Ken Finlay"
## [173] "Southern Right Charters"
## [174] "Tom Thomson"
## [175] "Siobhan Leachman"
## [176] "One news"
## [177] "April Harlin, Tim Markowvitz, Dusky project, Dennis Buurman"
## [178] "Pamela Le Noury"
## [179] "reported to Jamie Quirk, DOC"
## [180] "Dewald van Breda"
## [181] "Marina Costa"
## [182] "Gil Elimor"
## [183] "Ton Knijnenburg"
## [184] "wild_wind"
##
## $depth
## [1] 0 NA
##
## $locality
## [1] "Milford Sound"
## [2] "Falkland Islands"
## [3] "Auckland Islands"
## [4] NA
## [5] "Mouth of Lords River, Stewart I."
## [6] "Chubut, Argentina"
## [7] "South Head at Curio Bay"
## [8] "Lower Mahurangi Harbour"
## [9] "South Georgia and the South Sandwich Islands"
## [10] "South of Poor Knights Is"
## [11] "Rununder Pt, 1 n.m. SW"
## [12] "Lambton Harbour, , Wellington, NZ"
## [13] "St Kilda Beach"
## [14] "Antarctica"
## [15] "Awaroa Estuary mouth"
## [16] "Freshwater Basin, Milford Sound"
## [17] "Whirinaki, Hawkes Bay"
## [18] "Big Glory Bay, Stewart I."
## [19] "Ames St, Paekakariki 5034, New Zealand"
## [20] "Waikaranga, New Plymouth"
## [21] "Opoutama Beach, Mahia Peninsula"
## [22] "Paparoa coast, between Greymouth and Westport"
## [23] "Sandfly Beach"
## [24] "Santa Cruz, Argentina"
## [25] "Ocean Beach"
## [26] "Grey River mouth"
## [27] "Ackerís Point, Halfmoon Bay"
## [28] "3 Miles Reef off Taraunga, Bay of Plenty"
## [29] "Hicks Bay and Te Araroa"
## [30] "West of Nugget Point"
## [31] "Kaikoura"
## [32] "Western Cape, South Africa"
## [33] "Sinclair Head, south coast Wellington"
## [34] "Wellington, New Zealand"
## [35] "Wairoa-Mahia Peninsula"
## [36] "Ringa Ringa Beach and Ulva I., Paterson Inlet"
## [37] "Whangawehi"
## [38] "Bahia, Brazil"
## [39] "Wellington, NZ-WG, NZ"
## [40] "Perano Head"
## [41] "Gable End Foreland"
## [42] "Wainui Beach"
## [43] "Wellington Harbour"
## [44] "Stirling Point, entrance to Bluff Harbour"
## [45] "Taylorís Mistake"
## [46] "Te Wae Wae Bay"
## [47] "Waihua Bay"
## [48] "Wellington Urban Motorway, Pipitea, Wellington 6035, New Zealand"
## [49] "Palliser Bay"
## [50] "Mahia Beach"
## [51] "Buenos Aires, Argentina"
## [52] "Bayview"
## [53] "Karitane"
## [54] "Taiaroa Head"
## [55] "Anaura Bay"
## [56] "Bluff Harbour entrance"
## [57] "Whakatane Head"
## [58] "Whangarei Harbour"
## [59] "Coombe Rocks, 2 n.m. E"
## [60] "Tapuae Stream entrance south, New Plymouth"
## [61] "Glasgow Is"
## [62] "Rocky Bay, Tutukaka"
## [63] "Hares Ears, Doubtful Sound"
## [64] "about 10km off Karitane, north of Dunedin"
## [65] "Tahakopa Bay, Catlins"
## [66] "Brazil"
## [67] "Port Chalmers"
## [68] "Tory Channel"
## [69] "Pukearuhe, North Taranaki"
## [70] "Whakamahi Beach south of Wairoa"
## [71] "Bellblock, New Plymouth"
## [72] "Porangahau Beach"
## [73] "Bluff Harbour"
## [74] "Whakatane River"
## [75] "Otakou, Otago Harbour"
## [76] "Waikouiti Bay"
## [77] "Shag Point swimming north up Katiki Beach"
## [78] "Maupuia, Wellington 6022, New Zealand"
## [79] "Te Wae Wae Bay near Pahia Point"
## [80] "Ulva I., east side"
## [81] "Horseshoe Bay, Stewart I."
## [82] "Tuteremoana, Kapiti I."
## [83] "Torere to Otarawaire Bay"
## [84] "Moeraki"
## [85] "20 n.m. south of Cape Kidnappers"
## [86] "Pegasus near Albion, Stewart I., inside of Pearl I"
## [87] "Jackson Bay"
## [88] "Tomahawk Beach"
## [89] "St Clair Beach, Dunedin"
## [90] "Offshore New Plymouth"
## [91] "Bay of Islands"
## [92] "Taiaroa Head and harbour entrance"
## [93] "Maputo, Mozambique"
## [94] "Otago Harbour entrance"
## [95] "Long Pt, Mahia Peninsula"
## [96] "RingaRinga Beach"
## [97] "Parapara sandspit"
## [98] "Fighting Bay"
## [99] "near Whangarei Heads"
## [100] "57-61 Cable St, Te Aro, Wellington 6011, New Zealand"
## [101] "Mt Maunganui"
## [102] "East Cape, Stewart I."
## [103] "Whakatane Head, Mt Maunganui"
## [104] "Houghton Bay"
## [105] "Doubtless Bay"
## [106] "Little Port Cooper"
## [107] "Santa Catarina, Brazil"
## [108] "Thule and Fredís Camp"
## [109] "In coastal bays north of Gisborne"
## [110] "Port Taranaki"
## [111] "1 n.m. off Taiaroa Head"
## [112] "Mouth of Lyvia River, Doubtful Sound"
## [113] "Port William, Stewart I."
## [114] "Black Rocks, Bay of Islands"
## [115] "Shag Point"
## [116] "S of White I."
## [117] "Butterfield Beach, Halfmoon Bay, Stewart I."
## [118] "Port of Napier"
## [119] "North Beach Cobden and Blaketown Beach"
## [120] "Bay of Mahia Beach, Mahia Peninsula"
## [121] "Colac Bay"
## [122] "Mahia Peninsula"
## [123] "Buenos Aires F.D., Argentina"
## [124] "Mohaka River"
## [125] "Orutua River mouth, East Cape"
## [126] "South Taranaki Bight, , Wellington, NZ"
## [127] "Outside Otago Harbour entrance"
## [128] "St Kilda"
## [129] "Hen and Chickens Is"
## [130] "Whirinaki"
## [131] "Oriental Bay, , Wellington, NZ"
## [132] "Aramoana mole"
## [133] "Akaroa"
## [134] "Southside, Banks Peninsula"
## [135] "Otago Harbour"
## [136] "Mt Maunganui to Opotiki"
## [137] "Queensland, Australia"
## [138] "1 n.m. off Port Taranaki"
## [139] "Birdlings Flat, Canterbury"
## [140] "Taraunga Harbour"
## [141] "15 n.m. offshore of Motonui"
## [142] "Knife and Steel Harbour, between Big River and Waitutu River"
## [143] "Tierra del Fuego, Argentina"
## [144] "Brighton Beach"
## [145] "less than half a mile off-shore at Maraetai, near Auckland"
## [146] "Karoro"
## [147] "Army Bay, Whagaparaoa Peninsula"
## [148] "Porpoise Bay, Catlins"
## [149] "Clifton, Napier South"
## [150] "Victory Beach"
## [151] "Port Pegasus, Stewart I."
## [152] "3 n.m. N off Taiaroa Head"
## [153] "Tauranga"
## [154] "Le Bons Bay"
## [155] "SE of Taputeranga I., Island Bay"
## [156] "Baring Head, east of Wellington Harbour"
## [157] "Papanui Beach"
## [158] "Off Taiaroa Head, then Long Beach"
## [159] "Murray River, Stewart I."
## [160] "Dryden Bay, Endeavour Inlet; Clova Bay"
## [161] "Curio Bay"
## [162] "Oriental Bay, 6011, New Zealand"
## [163] "Hickís Bay wharf"
## [164] "Inside Bluff Harbour"
## [165] "Tahaenui Beach, north of Whakaki"
## [166] "Lyall Bay"
## [167] "Port Underwood, 3 n.m. ENE"
## [168] "Paterson Inlet, Stewart I."
## [169] "Westshore and Bayview"
## [170] "Bayview, Westshore, Napier"
## [171] "Sumner"
## [172] "Omaui"
## [173] "Christchurch"
## [174] "Wellington, Wellington, New Zealand"
## [175] "New Plymouth"
## [176] "Goose Bay to South Bay, Kaikoura"
## [177] "Beacon Pt, Bluff"
## [178] "Tolaga Bay wharf"
## [179] "Blackís Beach, Mahia Peninsula"
## [180] "Off Warrington Beach"
##
## $date_year
## [1] 1997 2021 1998 2009 1995 2014 2000 2008 1992 2010 2018 1988 1994 2016 1996
## [16] 1980 NA 2002 1991 2004 2020 1993 2019 2001 2006 2015 1999 2017 2007 1963
## [31] 2013 2012 2003 2011 1976 1990 1981 1983 1989
##
## $individualCount
## [1] "1" "2" "5" "4" "3" NA "8" "23" "10" "6"
##
## $sex
## [1] NA "m"# filtro final
franca_obis2 <- franca_obis1 %>%
filter(!flags %in% c("ON_LAND,NO_DEPTH","no_depth,on_land","depth_exceeds_bath,on_land","on_land,no_depth", "on_land", "on_land,depth_exceeds_bath", "ON_LAND", "ON_LAND,DEPTH_EXCEEDS_BATH"),
!is.na(datasetName),
!waterBody %in% c("world","Global,French EEZ"))O primeiro mapa refere-se ao conjunto de dados franca_obis1, antes da aplicação do filtro final e remoção das flagssinalizadas.
# baixar mapa do mundo
world <- map_data('world')
# plotar mapa franca obis 1
ggplot() +
geom_polygon(data = world, aes(x = long, y = lat, group = group)) +
coord_fixed() +
theme_classic() +
geom_point(data = franca_obis1, aes(x = decimalLongitude, y = decimalLatitude, color = waterBody)) +
#theme(legend.title = element_blank()) +
labs(x = "longitude", y = "latitude", title = expression(italic("Eubalaena australis")))
O segundo mapa contém menos observações (1020) e apresenta uma ocorrência mais pontual dos especimes ao longo do Hemisfério Sul.
# plotar mapa franca obis 2
ggplot() +
geom_polygon(data = world, aes(x = long, y = lat, group = group)) +
coord_fixed() +
theme_classic() +
geom_point(data = franca_obis2, aes(x = decimalLongitude, y = decimalLatitude, color = waterBody)) +
#theme(legend.title = element_blank()) +
labs(x = "longitude", y = "latitude", title = expression(italic("Eubalaena australis")))
2.2 Banco de dados GBIF
Para coletarmos informações deste repositório precisamos do pacote rgbif.
##Instalando pacote rgbif##
library(rgbif)Em seguida, iremos baixar as ocorrências da nossa espécie que constam no repositório GBIF para que possamos realizar os passos de limpeza dos dados.
# baixar ocorrencias
franca_gbif <- occ_data(scientificName = "Eubalaena australis",
hasCoordinate = TRUE,
hasGeospatialIssue=FALSE)## dimensoes
dim(franca_gbif)## NULLdim(franca_gbif$data)## [1] 500 117# checar campos
franca_gbif$data %>% names## [1] "key"
## [2] "scientificName"
## [3] "decimalLatitude"
## [4] "decimalLongitude"
## [5] "issues"
## [6] "datasetKey"
## [7] "publishingOrgKey"
## [8] "networkKeys"
## [9] "installationKey"
## [10] "publishingCountry"
## [11] "protocol"
## [12] "lastCrawled"
## [13] "lastParsed"
## [14] "crawlId"
## [15] "hostingOrganizationKey"
## [16] "basisOfRecord"
## [17] "individualCount"
## [18] "occurrenceStatus"
## [19] "taxonKey"
## [20] "kingdomKey"
## [21] "phylumKey"
## [22] "classKey"
## [23] "orderKey"
## [24] "familyKey"
## [25] "genusKey"
## [26] "speciesKey"
## [27] "acceptedTaxonKey"
## [28] "acceptedScientificName"
## [29] "kingdom"
## [30] "phylum"
## [31] "order"
## [32] "family"
## [33] "genus"
## [34] "species"
## [35] "genericName"
## [36] "specificEpithet"
## [37] "taxonRank"
## [38] "taxonomicStatus"
## [39] "iucnRedListCategory"
## [40] "dateIdentified"
## [41] "coordinatePrecision"
## [42] "coordinateUncertaintyInMeters"
## [43] "waterBody"
## [44] "year"
## [45] "month"
## [46] "day"
## [47] "eventDate"
## [48] "modified"
## [49] "lastInterpreted"
## [50] "license"
## [51] "isInCluster"
## [52] "geodeticDatum"
## [53] "class"
## [54] "countryCode"
## [55] "country"
## [56] "rightsHolder"
## [57] "associatedReferences"
## [58] "gbifID"
## [59] "type"
## [60] "taxonRemarks"
## [61] "catalogNumber"
## [62] "vernacularName"
## [63] "institutionCode"
## [64] "eventTime"
## [65] "identificationRemarks"
## [66] "georeferencedDate"
## [67] "recordNumber"
## [68] "identifier"
## [69] "nomenclaturalCode"
## [70] "verbatimEventDate"
## [71] "footprintWKT"
## [72] "locality"
## [73] "datasetName"
## [74] "collectionCode"
## [75] "occurrenceID"
## [76] "recordedBy"
## [77] "ownerInstitutionCode"
## [78] "datasetID"
## [79] "occurrenceRemarks"
## [80] "bibliographicCitation"
## [81] "stateProvince"
## [82] "references"
## [83] "http://unknown.org/nick"
## [84] "verbatimLocality"
## [85] "taxonID"
## [86] "http://unknown.org/occurrenceDetails"
## [87] "rights"
## [88] "identifiedBy"
## [89] "identificationID"
## [90] "lifeStage"
## [91] "informationWithheld"
## [92] "http://unknown.org/northing"
## [93] "language"
## [94] "locationRemarks"
## [95] "taxonConceptID"
## [96] "http://unknown.org/easting"
## [97] "http://unknown.org/zone"
## [98] "http://unknown.org/taxonRankID"
## [99] "locationID"
## [100] "http://unknown.org/species"
## [101] "identificationVerificationStatus"
## [102] "sex"
## [103] "dynamicProperties"
## [104] "reproductiveCondition"
## [105] "establishmentMeans"
## [106] "eventID"
## [107] "verbatimSRS"
## [108] "verbatimCoordinateSystem"
## [109] "samplingProtocol"
## [110] "depth"
## [111] "depthAccuracy"
## [112] "startDayOfYear"
## [113] "organismID"
## [114] "organismRemarks"
## [115] "continent"
## [116] "higherClassification"
## [117] "name"Após checar os dados iremos observar quais os principais issuesinformados pelo repositório. Esta estapa nos auxiliará na filtragem dos dados.
# Checar issus
gbif_issues()## code issue
## 1 bri BASIS_OF_RECORD_INVALID
## 2 ccm CONTINENT_COUNTRY_MISMATCH
## 3 cdc CONTINENT_DERIVED_FROM_COORDINATES
## 4 conti CONTINENT_INVALID
## 5 cdiv COORDINATE_INVALID
## 6 cdout COORDINATE_OUT_OF_RANGE
## 7 cdrep COORDINATE_REPROJECTED
## 8 cdrepf COORDINATE_REPROJECTION_FAILED
## 9 cdreps COORDINATE_REPROJECTION_SUSPICIOUS
## 10 cdround COORDINATE_ROUNDED
## 11 cucdmis COUNTRY_COORDINATE_MISMATCH
## 12 cudc COUNTRY_DERIVED_FROM_COORDINATES
## 13 cuiv COUNTRY_INVALID
## 14 cum COUNTRY_MISMATCH
## 15 depmms DEPTH_MIN_MAX_SWAPPED
## 16 depnn DEPTH_NON_NUMERIC
## 17 depnmet DEPTH_NOT_METRIC
## 18 depunl DEPTH_UNLIKELY
## 19 elmms ELEVATION_MIN_MAX_SWAPPED
## 20 elnn ELEVATION_NON_NUMERIC
## 21 elnmet ELEVATION_NOT_METRIC
## 22 elunl ELEVATION_UNLIKELY
## 23 gass84 GEODETIC_DATUM_ASSUMED_WGS84
## 24 gdativ GEODETIC_DATUM_INVALID
## 25 iddativ IDENTIFIED_DATE_INVALID
## 26 iddatunl IDENTIFIED_DATE_UNLIKELY
## 27 mdativ MODIFIED_DATE_INVALID
## 28 mdatunl MODIFIED_DATE_UNLIKELY
## 29 muldativ MULTIMEDIA_DATE_INVALID
## 30 muluriiv MULTIMEDIA_URI_INVALID
## 31 preneglat PRESUMED_NEGATED_LATITUDE
## 32 preneglon PRESUMED_NEGATED_LONGITUDE
## 33 preswcd PRESUMED_SWAPPED_COORDINATE
## 34 rdativ RECORDED_DATE_INVALID
## 35 rdatm RECORDED_DATE_MISMATCH
## 36 rdatunl RECORDED_DATE_UNLIKELY
## 37 refuriiv REFERENCES_URI_INVALID
## 38 txmatfuz TAXON_MATCH_FUZZY
## 39 txmathi TAXON_MATCH_HIGHERRANK
## 40 txmatnon TAXON_MATCH_NONE
## 41 typstativ TYPE_STATUS_INVALID
## 42 zerocd ZERO_COORDINATE
## 43 cdpi COORDINATE_PRECISION_INVALID
## 44 cdumi COORDINATE_UNCERTAINTY_METERS_INVALID
## 45 indci INDIVIDUAL_COUNT_INVALID
## 46 interr INTERPRETATION_ERROR
## 47 iccos INDIVIDUAL_COUNT_CONFLICTS_WITH_OCCURRENCE_STATUS
## 48 osiic OCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
## 49 osu OCCURRENCE_STATUS_UNPARSABLE
## 50 geodi GEOREFERENCED_DATE_INVALID
## 51 geodu GEOREFERENCED_DATE_UNLIKELY
## 52 ambcol AMBIGUOUS_COLLECTION
## 53 ambinst AMBIGUOUS_INSTITUTION
## 54 colmafu COLLECTION_MATCH_FUZZY
## 55 colmano COLLECTION_MATCH_NONE
## 56 incomis INSTITUTION_COLLECTION_MISMATCH
## 57 inmafu INSTITUTION_MATCH_FUZZY
## 58 inmano INSTITUTION_MATCH_NONE
## 59 osifbor OCCURRENCE_STATUS_INFERRED_FROM_BASIS_OF_RECORD
## 60 diffown DIFFERENT_OWNER_INSTITUTION
## 61 taxmatagg TAXON_MATCH_AGGREGATE
## 62 fpsrsinv FOOTPRINT_SRS_INVALID
## 63 fpwktinv FOOTPRINT_WKT_INVALID
## 64 anm ACCEPTED_NAME_MISSING
## 65 annu ACCEPTED_NAME_NOT_UNIQUE
## 66 anuidi ACCEPTED_NAME_USAGE_ID_INVALID
## 67 aitidinv ALT_IDENTIFIER_INVALID
## 68 bbmn BACKBONE_MATCH_NONE
## 69 basauthm BASIONYM_AUTHOR_MISMATCH
## 70 bibrinv BIB_REFERENCE_INVALID
## 71 chsun CHAINED_SYNOYM
## 72 clasna CLASSIFICATION_NOT_APPLIED
## 73 clasroi CLASSIFICATION_RANK_ORDER_INVALID
## 74 conbascomb CONFLICTING_BASIONYM_COMBINATION
## 75 desinv DESCRIPTION_INVALID
## 76 disinv DISTRIBUTION_INVALID
## 77 hom HOMONYM
## 78 minv MULTIMEDIA_INVALID
## 79 npm NAME_PARENT_MISMATCH
## 80 ns NO_SPECIES
## 81 nsinv NOMENCLATURAL_STATUS_INVALID
## 82 onder ORIGINAL_NAME_DERIVED
## 83 onnu ORIGINAL_NAME_NOT_UNIQUE
## 84 onuidinv ORIGINAL_NAME_USAGE_ID_INVALID
## 85 ov ORTHOGRAPHIC_VARIANT
## 86 pc PARENT_CYCLE
## 87 pnnu PARENT_NAME_NOT_UNIQUE
## 88 pnuidinv PARENT_NAME_USAGE_ID_INVALID
## 89 pp PARTIALLY_PARSABLE
## 90 pbg PUBLISHED_BEFORE_GENUS
## 91 rankinv RANK_INVALID
## 92 relmiss RELATIONSHIP_MISSING
## 93 scina SCIENTIFIC_NAME_ASSEMBLED
## 94 spprinv SPECIES_PROFILE_INVALID
## 95 taxstinv TAXONOMIC_STATUS_INVALID
## 96 taxstmis TAXONOMIC_STATUS_MISMATCH
## 97 unpars UNPARSABLE
## 98 vernnameinv VERNACULAR_NAME_INVALID
## 99 backmatagg BACKBONE_MATCH_AGGREGATE
## description
## 1 The given basis of record is impossible to interpret or seriously different from the recommended vocabulary.
## 2 The interpreted continent and country do not match up.
## 3 The interpreted continent is based on the coordinates, not the verbatim string information.
## 4 Uninterpretable continent values found.
## 5 Coordinate value given in some form but GBIF is unable to interpret it.
## 6 Coordinate has invalid lat/lon values out of their decimal max range.
## 7 The original coordinate was successfully reprojected from a different geodetic datum to WGS84.
## 8 The given decimal latitude and longitude could not be reprojected to WGS84 based on the provided datum.
## 9 Indicates successful coordinate reprojection according to provided datum, but which results in a datum shift larger than 0.1 decimal degrees.
## 10 Original coordinate modified by rounding to 5 decimals.
## 11 The interpreted occurrence coordinates fall outside of the indicated country.
## 12 The interpreted country is based on the coordinates, not the verbatim string information.
## 13 Uninterpretable country values found.
## 14 Interpreted country for dwc:country and dwc:countryCode contradict each other.
## 15 Set if supplied min>max
## 16 Set if depth is a non numeric value
## 17 Set if supplied depth is not given in the metric system, for example using feet instead of meters
## 18 Set if depth is larger than 11.000m or negative.
## 19 Set if supplied min > max elevation
## 20 Set if elevation is a non numeric value
## 21 Set if supplied elevation is not given in the metric system, for example using feet instead of meters
## 22 Set if elevation is above the troposphere (17km) or below 11km (Mariana Trench).
## 23 Indicating that the interpreted coordinates assume they are based on WGS84 datum as the datum was either not indicated or interpretable.
## 24 The geodetic datum given could not be interpreted.
## 25 The date given for dwc:dateIdentified is invalid and cant be interpreted at all.
## 26 The date given for dwc:dateIdentified is in the future or before Linnean times (1700).
## 27 A (partial) invalid date is given for dc:modified, such as a non existing date, invalid zero month, etc.
## 28 The date given for dc:modified is in the future or predates unix time (1970).
## 29 An invalid date is given for dc:created of a multimedia object.
## 30 An invalid uri is given for a multimedia object.
## 31 Latitude appears to be negated, e.g. 32.3 instead of -32.3
## 32 Longitude appears to be negated, e.g. 32.3 instead of -32.3
## 33 Latitude and longitude appear to be swapped.
## 34 A (partial) invalid date is given, such as a non existing date, invalid zero month, etc.
## 35 The recording date specified as the eventDate string and the individual year, month, day are contradicting.
## 36 The recording date is highly unlikely, falling either into the future or represents a very old date before 1600 that predates modern taxonomy.
## 37 An invalid uri is given for dc:references.
## 38 Matching to the taxonomic backbone can only be done using a fuzzy, non exact match.
## 39 Matching to the taxonomic backbone can only be done on a higher rank and not the scientific name.
## 40 Matching to the taxonomic backbone cannot be done cause there was no match at all or several matches with too little information to keep them apart (homonyms).
## 41 The given type status is impossible to interpret or seriously different from the recommended vocabulary.
## 42 Coordinate is the exact 0/0 coordinate, often indicating a bad null coordinate.
## 43 Indicates an invalid or very unlikely coordinatePrecision
## 44 Indicates an invalid or very unlikely dwc:uncertaintyInMeters.
## 45 Individual count value not parsable into an integer.
## 46 An error occurred during interpretation, leaving the record interpretation incomplete.
## 47 Example: individual count value > 0, but occurrence status is absent and etc.
## 48 Occurrence status was inferred from the individual count value
## 49 Occurrence status value can't be assigned to OccurrenceStatus
## 50 The date given for dwc:georeferencedDate is invalid and can't be interpreted at all.
## 51 The date given for dwc:georeferencedDate is in the future or before Linnean times (1700).
## 52 The given collection matches with more than 1 GrSciColl collection.
## 53 The given institution matches with more than 1 GrSciColl institution.
## 54 The given collection was fuzzily matched to a GrSciColl collection.
## 55 The given collection couldn't be matched with any GrSciColl collection.
## 56 The collection matched doesn't belong to the institution matched.
## 57 The given institution was fuzzily matched to a GrSciColl institution.
## 58 The given institution couldn't be matched with any GrSciColl institution.
## 59 Occurrence status was inferred from basis of records
## 60 The given owner institution is different than the given institution. Therefore we assume it doesn't belong to the institution and we don't link it to the occurrence.
## 61 Matching to the taxonomic backbone can only be done on a species level, but the occurrence was in fact considered a broader species aggregate/complex.
## 62 The Footprint Spatial Reference System given could not be interpreted
## 63 The Footprint Well-Known-Text given could not be interpreted
## 64 Synonym lacking an accepted name.
## 65 Synonym has a verbatim accepted name which is not unique and refers to several records.
## 66 The value for dwc:acceptedNameUsageID could not be resolved.
## 67 At least one alternative identifier extension record attached to this name usage is invalid.
## 68 Name usage could not be matched to the GBIF backbone.
## 69 The authorship of the original name does not match the authorship in brackets of the actual name.
## 70 At least one bibliographic reference extension record attached to this name usage is invalid.
## 71 If a synonym points to another synonym as its accepted taxon the chain is resolved.
## 72 The denormalized classification could not be applied to the name usage.
## 73 The given ranks of the names in the classification hierarchy do not follow the hierarchy of ranks.
## 74 There have been more than one accepted name in a homotypical basionym group of names.
## 75 At least one description extension record attached to this name usage is invalid.
## 76 At least one distribution extension record attached to this name usage is invalid.
## 77 A not synonymized homonym exists for this name in some other backbone source which have been ignored at build time.
## 78 At least one multimedia extension record attached to this name usage is invalid.
## 79 The (accepted) bi/trinomial name does not match the parent name and should be recombined into the parent genus/species.
## 80 The group (currently only genera are tested) are lacking any accepted species GBIF backbone specific issue.
## 81 dwc:nomenclaturalStatus could not be interpreted
## 82 Record has a original name (basionym) relationship which was derived from name & authorship comparison, but did not exist explicitly in the data.
## 83 Record has a verbatim original name (basionym) which is not unique and refers to several records.
## 84 The value for dwc:originalNameUsageID could not be resolved.
## 85 A potential orthographic variant exists in the backbone.
## 86 The child parent classification resulted into a cycle that needed to be resolved/cut.
## 87 Record has a verbatim parent name which is not unique and refers to several records.
## 88 The value for dwc:parentNameUsageID could not be resolved.
## 89 The beginning of the scientific name string was parsed, but there is additional information in the string that was not understood.
## 90 A bi/trinomial name published earlier than the parent genus was published.
## 91 dwc:taxonRank could not be interpreted
## 92 There were problems representing all name usage relationships, i.e.
## 93 The scientific name was assembled from the individual name parts and not given as a whole string.
## 94 At least one species profile extension record attached to this name usage is invalid.
## 95 dwc:taxonomicStatus could not be interpreted
## 96 no description
## 97 The scientific name string could not be parsed at all, but appears to be a parsable name type, i.e.
## 98 At least one vernacular name extension record attached to this name usage is invalid.
## 99 Name usage could only be matched to a GBIF backbone species, but was in fact a broader species aggregate/complex.
## type
## 1 occurrence
## 2 occurrence
## 3 occurrence
## 4 occurrence
## 5 occurrence
## 6 occurrence
## 7 occurrence
## 8 occurrence
## 9 occurrence
## 10 occurrence
## 11 occurrence
## 12 occurrence
## 13 occurrence
## 14 occurrence
## 15 occurrence
## 16 occurrence
## 17 occurrence
## 18 occurrence
## 19 occurrence
## 20 occurrence
## 21 occurrence
## 22 occurrence
## 23 occurrence
## 24 occurrence
## 25 occurrence
## 26 occurrence
## 27 occurrence
## 28 occurrence
## 29 occurrence
## 30 occurrence
## 31 occurrence
## 32 occurrence
## 33 occurrence
## 34 occurrence
## 35 occurrence
## 36 occurrence
## 37 occurrence
## 38 occurrence
## 39 occurrence
## 40 occurrence
## 41 occurrence
## 42 occurrence
## 43 occurrence
## 44 occurrence
## 45 occurrence
## 46 occurrence
## 47 occurrence
## 48 occurrence
## 49 occurrence
## 50 occurrence
## 51 occurrence
## 52 occurrence
## 53 occurrence
## 54 occurrence
## 55 occurrence
## 56 occurrence
## 57 occurrence
## 58 occurrence
## 59 occurrence
## 60 occurrence
## 61 occurrence
## 62 occurrence
## 63 occurrence
## 64 name
## 65 name
## 66 name
## 67 name
## 68 name
## 69 name
## 70 name
## 71 name
## 72 name
## 73 name
## 74 name
## 75 name
## 76 name
## 77 name
## 78 name
## 79 name
## 80 name
## 81 name
## 82 name
## 83 name
## 84 name
## 85 name
## 86 name
## 87 name
## 88 name
## 89 name
## 90 name
## 91 name
## 92 name
## 93 name
## 94 name
## 95 name
## 96 name
## 97 name
## 98 name
## 99 name# checar os issues individuais da espécie
issues_gbif <- franca_gbif$data$issues %>%
# unique() %>%
strsplit(.,"[,]") %>%
unlist() %>%
unique()
issues_gbif## [1] "cudc" "fpwktinv" "cdround" "osiic"O próximo passo é selecionar os campos de interesse para reduzirmos a quantidade de dados a serem analisados.
# selecionar campos de interesse
franca_gbif1 <- franca_gbif$data %>%
dplyr::select(scientificName, decimalLatitude, decimalLongitude,issues,
basisOfRecord, sex, rightsHolder,continent, year, month, day,
datasetName, recordedBy, waterBody, country, iucnRedListCategory, countryCode, depth)Nosso conjunto de dados franca_gbif1contêm 500 observações, distribuidas em 18 variáveis. No entanto, algumas observações podem estar duplicadas, para garantir a qualidade dos dados iremos selecionar as ocorrências únicas.
# ocorrencias únicas
franca_gbif1 <- franca_gbif1 %>%
distinct()Observe agora que as observações foram reduzidas para 222. Prosseguindo com as análises iremos investigar os níveis suspeitos.
# checar niveis dos fatores
lapply(franca_gbif1, unique)## $scientificName
## [1] "Eubalaena australis (Desmoulins, 1822)"
##
## $decimalLatitude
## [1] -34.03667 -34.02305 -52.39043 -52.39074 -34.05467 -37.35790 -34.23739
## [8] -35.54274 -51.68076 -51.68251 -51.67930 -52.40948 -51.60000 -35.53844
## [15] -51.67955 -51.68168 -51.67368 -51.68166 -51.68184 -51.68166 -51.68232
## [22] -51.68445 -51.66459 -51.67864 -51.67991 -51.67762 -35.12843 -35.14821
## [29] -35.13279 -35.33007 -35.13122 -35.41193 -35.42651 -33.86091 -26.32973
## [36] -34.32450 -34.85804 -14.76130 -53.41291 -53.36049 -54.00860 -51.46661
## [43] -51.46651 -54.04974 -54.05698 -54.02070 -51.42980 -38.40381 -37.26004
## [50] -35.52269 -35.10000 -51.67101 -51.66574 -51.65392 -43.56617 -33.99947
## [57] -38.01873 -43.58046 -43.50516 -34.42103 -27.96022 -42.58630 -42.61477
## [64] -42.58703 -40.81476 -42.59547 -42.64539 -34.45263 -42.65840 -42.58745
## [71] -42.65837 -42.64540 -42.59548 -42.58565 -42.65837 -42.58732 -42.77256
## [78] -42.58599 -41.99756 -42.60843 -42.65837 -42.58641 -41.99990 -41.99743
## [85] -42.59543 -42.58695 -42.58668 -42.58751 -41.99764 -42.58566 -42.58730
## [92] -42.58841 -42.58564 -42.59054 -40.81477 -42.64543 -42.58842 -42.58785
## [99] -42.07889 -42.58875 -42.58865 -42.64537 -42.58559 -42.58874 -42.58446
## [106] -42.07849 -42.58736 -42.58558 -42.58488 -42.58387 -42.58749 -42.58540
## [113] -42.58867 -42.58750 -42.60851 -42.58588 -42.79327 -34.45064 -42.58518
## [120] -42.60840 -42.58926 -42.59035 -42.58692 -42.58720 -34.00168 -34.00502
## [127] -38.44038 -34.86352 -34.00129 -34.03890 -34.10512 -34.01992 -60.37715
## [134] -53.40609 -52.55004 -46.06423 -40.25659 -40.22642 -53.28498 -61.70171
## [141] -40.68550 -53.38298 -54.03643 -54.02000 -53.61125 -54.20000 -34.90387
## [148] -35.17015 -33.86275 -35.16810 -35.55052 -32.02997 -38.21291 -31.94997
## [155] -33.53330 -35.52762 -38.20000 -33.42130 -34.15108 -34.50000 -38.58706
## [162] -33.49634 -34.15611 -45.79519 -35.56000 -51.39355 -45.63600 -64.14277
## [169] -53.17382 -54.01584 -54.14200 -34.18141 -34.18252 -34.31786 -31.58611
## [176] -31.67639 -46.23440 -34.25437 -34.57088 -34.57086 -34.07506 -31.51194
## [183] -31.49361 -31.72944
##
## $decimalLongitude
## [1] 18.30278 18.28611 -68.41346 -68.41257 22.26884 -57.00126 136.27124
## [8] 138.69163 -57.76472 -57.71751 -57.79563 -68.41315 -57.80000 138.68394
## [15] -57.77169 -57.71871 -57.78936 -57.71863 -57.71821 -57.71905 -57.71753
## [22] -57.72014 -57.75957 -57.75064 -57.72158 -57.77492 138.46390 138.46509
## [29] 138.46806 138.44433 138.47011 138.32634 138.31984 119.95535 -48.50746
## [36] 150.92547 150.63703 -38.97340 -37.27575 -37.89648 -37.35193 -57.83537
## [43] -57.83519 -37.25717 -37.42276 -57.86239 142.50814 150.05366 138.73644
## [50] 138.50000 -57.74018 -57.77297 -57.80163 172.77025 22.56654 -57.52326
## [57] 172.77850 172.73979 20.85549 -48.62422 -64.29320 -64.90929 -64.29275
## [64] -65.09298 -64.81452 -64.96911 20.61534 -64.98665 -64.29381 -64.98668
## [71] -64.81454 -64.29384 -64.98669 -64.29395 -65.02736 -64.29357 -65.07020
## [78] -64.98671 -64.81455 -64.83351 -64.98668 -64.29308 -65.06747 -65.06947
## [85] -64.81452 -64.29274 -64.29279 -64.29443 -65.06940 -64.30854 -64.29403
## [92] -64.29475 -64.30853 -64.30593 -65.09300 -64.96916 -64.81456 -64.29484
## [99] -64.29384 -63.75729 -64.29444 -64.29457 -64.96915 -64.29232 -64.29277
## [106] -64.28784 -63.75761 -64.29349 -64.29525 -64.29488 -64.28906 -64.29443
## [113] -64.29519 -64.29736 -64.29433 -64.83339 -64.29369 -64.94972 20.70034
## [120] -64.29377 -64.83352 -64.29952 -64.30607 -64.29693 -64.29715 22.60141
## [127] 22.60532 144.17449 135.71910 22.60592 119.57697 23.11501 23.90394
## [134] -51.85442 -44.68447 -50.21689 166.65746 -57.81189 -58.21984 -43.42955
## [141] -51.57980 -58.01557 -43.46257 -36.80568 -36.48000 -41.84692 -36.00000
## [148] 118.23315 117.81876 121.83911 117.93971 138.63304 132.47134 145.03671
## [155] 132.48396 151.38242 138.69473 145.00000 115.03766 18.43988 19.23000
## [162] -58.73412 115.06091 18.43805 170.71202 138.63000 -57.73517 170.79300
## [169] -60.92973 -44.55735 -38.12882 -36.56770 18.35450 18.35618 18.46090
## [176] 131.31306 131.17306 167.01440 119.51929 19.35049 19.35061 22.81726
## [183] 131.20250 131.22194 131.30306
##
## $issues
## [1] "cudc,fpwktinv" "cdround" "" "fpwktinv"
## [5] "cdround,cudc" "cdround,osiic"
##
## $basisOfRecord
## [1] "HUMAN_OBSERVATION"
##
## $sex
## [1] NA "FEMALE"
##
## $rightsHolder
## [1] "Daniela Abras"
## [2] "Santiago Imberti"
## [3] "bernie2u2"
## [4] "Francisco González Táboas"
## [5] "covegirl"
## [6] "Marianne Broug"
## [7] "Sue Luxton"
## [8] "littlellama"
## [9] "Martin Anstee"
## [10] "Sara Jenner"
## [11] "Ella Crowie"
## [12] "Mark"
## [13] "Nikki"
## [14] "pamwhetnall"
## [15] "Chris"
## [16] "Matt Tank"
## [17] "Warwick Moyse"
## [18] "southseas"
## [19] "beardedvulture"
## [20] "David Muirhead"
## [21] "keenasfish"
## [22] "andersonwarkentin"
## [23] "Nicola Kennedy"
## [24] "martyhing"
## [25] "Ecosul Turismo"
## [26] "Jamie Coleman"
## [27] "duke_n"
## [28] "NSW Dept of Planning, Industry and Environment"
## [29] "philip-roetman"
## [30] NA
## [31] "Karina"
## [32] "babbieb"
## [33] "Barbii Pitarch"
## [34] "Adam Duchac"
## [35] "Gigi Laidler"
## [36] "Christian"
## [37] "Pablo Fraire"
## [38] "Nigel Forshaw"
## [39] "Mica Fraire"
## [40] "possumpete"
## [41] "Chris Seager"
## [42] "Em Lamond"
## [43] "alixpepsie"
## [44] "Matthew Fainman"
## [45] "Stefan Bernhard"
## [46] "Ton Knijnenburg"
## [47] "Lloyd Esler"
## [48] "boogan_boy"
## [49] "whale_nerd"
## [50] "Adrian Boyle"
## [51] "Rémi Bigonneau"
## [52] "Alain Bidart"
## [53] "Frank Tetreault"
## [54] "Javier Cotin"
## [55] "kdunnart"
## [56] "nishanw"
## [57] "epcruises"
## [58] "Sue Brabender"
## [59] "Simon Ramsey"
## [60] "Lewis Burnett"
## [61] "Charles Booysen"
## [62] "Dewald van Breda"
## [63] "joluno"
## [64] "Giverny"
## [65] "Gil Elimor"
## [66] "Conor Ryan"
## [67] "Ella Potts"
## [68] "Steph & Oli Prince"
## [69] "johnyeld"
## [70] "martine179"
## [71] "Reingart"
## [72] "Stichting Natuurinformatie"
##
## $continent
## [1] NA "AFRICA"
##
## $year
## [1] 2021 2020 2019
##
## $month
## [1] 1 3 4 5 6 7 8 9 2 10 12
##
## $day
## [1] 22 21 30 29 13 9 6 20 16 17 12 26 28 25 27 4 5 7 1 18 11 8 24 10 15
## [26] 23 2 14 31 19 3
##
## $datasetName
## [1] "Happywhale - Southern Right Whale in South Atlantic Ocean"
## [2] "Happywhale - Southern Right Whale in South Pacific Ocean"
## [3] "iNaturalist research-grade observations"
## [4] "DPIE Default Sightings"
## [5] NA
## [6] "Happywhale - Southern Right Whale in Southern Ocean"
## [7] "MBIS Marine Fauna and Flora observations around New Zealand"
##
## $recordedBy
## [1] "Daniela Abras"
## [2] "Santiago Imberti"
## [3] "bernie2u2"
## [4] "Francisco González Táboas"
## [5] "covegirl"
## [6] "Marianne Broug"
## [7] "Sue Luxton"
## [8] "littlellama"
## [9] "Martin Anstee"
## [10] "Sara Jenner"
## [11] "Ella Crowie"
## [12] "Mark"
## [13] "Nikki"
## [14] "pamwhetnall"
## [15] "Chris"
## [16] "Matt Tank"
## [17] "Warwick Moyse"
## [18] "southseas"
## [19] "beardedvulture"
## [20] "David Muirhead"
## [21] "keenasfish"
## [22] "andersonwarkentin"
## [23] "Nicola Kennedy"
## [24] "martyhing"
## [25] "Ecosul Turismo"
## [26] NA
## [27] "Jamie Coleman"
## [28] "duke_n"
## [29] "OIXR14040900"
## [30] "philip-roetman"
## [31] "<a href='https://bee.questagame.com/#/profile/17845?questagame_user_id=17845'>Surfap | questagame.com</a>"
## [32] "Karina"
## [33] "babbieb"
## [34] "Barbii Pitarch"
## [35] "Adam Duchac"
## [36] "Gigi Laidler"
## [37] "Christian"
## [38] "Pablo Fraire"
## [39] "Nigel Forshaw"
## [40] "Mica Fraire"
## [41] "possumpete"
## [42] "Chris Seager"
## [43] "Em Lamond"
## [44] "alixpepsie"
## [45] "Matthew Fainman"
## [46] "Stefan Bernhard"
## [47] "Ton Knijnenburg"
## [48] "Lloyd Esler"
## [49] "boogan_boy"
## [50] "whale_nerd"
## [51] "Adrian Boyle"
## [52] "Rémi Bigonneau"
## [53] "Alain Bidart"
## [54] "Frank Tetreault"
## [55] "Javier Cotin"
## [56] "kdunnart"
## [57] "nishanw"
## [58] "epcruises"
## [59] "Sue Brabender"
## [60] "ODXB02011601"
## [61] "Simon Ramsey"
## [62] "<a href='https://bee.questagame.com/#/profile/41498?questagame_user_id=41498'>winnerwinnerchickendinner | questagame.com</a>"
## [63] "Lewis Burnett"
## [64] "Charles Booysen"
## [65] "Dewald van Breda"
## [66] "joluno"
## [67] "Giverny"
## [68] "Marsh, O. Olivia"
## [69] "Gil Elimor"
## [70] "Conor Ryan"
## [71] "Ella Potts"
## [72] "Steph & Oli Prince"
## [73] "johnyeld"
## [74] "martine179"
## [75] "Reingart"
## [76] "Christiansen, F. Fredrik|Henderson, A. Anus"
## [77] "Mair, C. Callum"
## [78] "Henderson, A. Anus"
##
## $waterBody
## [1] "South Atlantic Ocean" "South Pacific Ocean" NA
## [4] "Southern Ocean" "Pacific Ocean"
##
## $country
## [1] "South Africa"
## [2] "Argentina"
## [3] "Australia"
## [4] "Falkland Islands (Malvinas)"
## [5] "Brazil"
## [6] "South Georgia and the South Sandwich Islands"
## [7] "New Zealand"
## [8] "Antarctica"
## [9] NA
##
## $iucnRedListCategory
## [1] "LC"
##
## $countryCode
## [1] "ZA" "AR" "AU" "FK" "BR" "GS" "NZ" "AQ" NA
##
## $depth
## [1] NA 0# investigar niveis suspeitos
franca_gbif1 %>%
distinct(country) %>%
pull()## [1] "South Africa"
## [2] "Argentina"
## [3] "Australia"
## [4] "Falkland Islands (Malvinas)"
## [5] "Brazil"
## [6] "South Georgia and the South Sandwich Islands"
## [7] "New Zealand"
## [8] "Antarctica"
## [9] NA# country
franca_gbif1 %>%
group_by(country) %>%
summarise(occ = length(scientificName)) %>%
ggplot(aes(occ, y=country)) +
geom_bar(stat = 'identity')
A maioria das ocorrências registradas neste repositório foram na Argentina e Australia.
A fim de compreender melhor a distribuição de Eubalaena australis iremos unificar as ocorrências dos dois repositórios analisados: OBIS e GBIF. Antes precisaremos descobrir as diferenças entre as variáveis:
# unir GBIF e OBIS
# ver diferencas
setdiff(names(franca_gbif1), names(franca_obis2))## [1] "issues" "continent" "year"
## [4] "month" "day" "country"
## [7] "iucnRedListCategory" "countryCode"setdiff(names(franca_obis2), names(franca_gbif1))## [1] "bathymetry" "flags" "occurrenceStatus" "locality"
## [5] "date_year" "individualCount"# juntar os dados
franca_big <- bind_rows(franca_gbif1 %>%
mutate(repo = paste0("gbif", row.names(.))),
franca_obis2 %>%
mutate(repo = paste0("obis", row.names(.)))) %>%
column_to_rownames("repo") %>%
dplyr::select(decimalLongitude, decimalLatitude, depth) %>%
distinct() %>%
rownames_to_column("occ") %>%
separate(col = "occ", into = c("datasetName", "rn"), sep = 4) %>%
mutate(scientificName = "Eubalaena australis") %>%
dplyr::select(-rn)Nosso conjunto de dados unificado foi nomeado de franca_big. Nele constam 1130 observações com 5 variáveis. Vamos agora mapear a distribuição da nossa espécie por meio da latitude.
# mapear ocorrencias pela latitude
franca_big %>%
mutate(lat = round(decimalLatitude)) %>%
group_by(lat, scientificName) %>%
summarise(occ = length(scientificName)) %>%
ggplot(aes(y = occ, x = lat, color = scientificName)) +
geom_point() +
geom_smooth() +
theme_classic() +
labs(x = "latitude", y = 'ocorrências')
Podemos observar que não temos nenhuma ocorrência de Eubalaena australis acima de latitude -20º. Isso corrobora com a distribuição restrita desta espécie para o Hemisfério Sul, tendo sua maior concentração nas latitudes menores que -40º.
3 Aplicação de gráficos interativos
Os gráficos interativos permitem uma melhor observação dos pontos de ocorrência, além de se apresentar como um atrativo a mais para o site. Para se utilizar esta funcionalidade deve-se carregar o pacote leaflet
library(leaflet)# conferir no mapa
pal <- colorFactor(palette = "viridis", domain = unique(franca_big$datasetName))
franca_big %>%
leaflet() %>%
addTiles() %>%
addCircleMarkers(~decimalLongitude,
~decimalLatitude,
radius = 4,
label = ~as.character(datasetName),
color = ~pal(franca_big$datasetName),
stroke = FALSE, fillOpacity = 0.6)%>%
addLegend('bottomright',
colors = unique(pal(franca_big$datasetName)),
labels = unique(franca_big$datasetName),
title = 'Bases de Dados',
opacity = 0.6)Acima temos um exemplo com os dados unificados sobre nossa espécie alvo (dois repositórios). Podemos obsrrvar que alguns pontos de ocorrência se sobrepõem. Deste ponto em diante iremos utilizar os dados franca_obis2que apresentam maior quantidade de observações.
# conferir no mapa OBIS 2
pal2 <- colorFactor(palette = "viridis", domain = unique(franca_obis2$individualCount))
franca_obis2 %>%
leaflet() %>%
addTiles() %>%
addCircleMarkers(~decimalLongitude,
~decimalLatitude,
radius = 4,
label = ~as.character(locality),
color = ~pal2(franca_obis2$individualCount),
stroke = FALSE, fillOpacity = 0.6)%>%
addLegend('bottomright',
colors = unique(pal2(franca_obis2$individualCount)),
labels = unique(franca_obis2$individualCount),
title = 'Nº Indivíduos',
opacity = 0.6)Neste mapa classificamos os pontos de ocorrência pela quantidade de indivíduos ao longo de toda a distribuição de Eubalaena australis.
Outros gráficos podem ser elaborados utilizando a função Plotly para melhorar a interação entre as informações e apresentar mais funcionalidades aos gráficos, como no exemplo abaixo:
#plotar ocorrências ao longo do tempo
library(plotly)
fr <- franca_obis2 %>%
mutate(date = round(date_year)) %>%
group_by(date, waterBody) %>%
summarise(occ = length(scientificName)) %>%
ggplot(aes(y = occ, x = date, color = waterBody)) +
geom_point() +
theme_classic() +
labs(x = "Anos", y = 'Ocorrências')
ggplotly(fr)O pacote ggplotnos fornece a possibilidade de criarmos um gráfico animado. Sendo assim, utilizamos os dados do repositório OBIS e plotamos uma serie temporal de ocorrência da baleia franca austral, informando também dados como a profundidade e latitude de ocorrência:
#grafico animado
gg <- ggplot(franca_obis2, aes(decimalLatitude, waterBody, color= bathymetry)) +
geom_point(aes(frame = date_year, ids=locality))
ggplotly(gg)Enfim, compartilhe os dados e façamos o melhor para a ciência, meio ambiente e a sociedade.
